AI Product Launch Checklist
A comprehensive, battle-tested checklist for launching AI products successfully. From initial strategy through scaling and iteration.
Why This Checklist?
Launching an AI product is fundamentally different from traditional software launches. AI systems introduce unique challenges: model performance, data quality, ethical considerations, safety measures, and unpredictable behavior that requires careful monitoring and iteration.
This checklist distills lessons from multiple AI product launches—both successes and failures. It provides a structured roadmap to help you navigate the complexity, avoid common pitfalls, and launch with confidence. Whether you're building a B2B AI SaaS platform, a consumer AI app, or integrating AI features into an existing product, this guide will help you ship successfully.
What You'll Learn
Strategic Planning
Define clear goals, identify your target market, validate your AI use case, and build a launch strategy that sets you up for success.
Technical Foundation
Choose the right architecture, select appropriate models, design data pipelines, and build infrastructure that scales with your product.
Safety & Ethics
Implement bias detection, safety measures, compliance frameworks, and ethical guidelines to build responsible AI products.
Go-to-Market Strategy
Craft compelling messaging, execute your launch plan, acquire early users, and build momentum for your AI product.
Monitoring & Operations
Set up observability, track model performance, implement feedback loops, and respond to incidents effectively.
Scaling & Iteration
Optimize performance and costs, improve model accuracy, scale infrastructure, and iterate based on real-world usage data.
Who This Checklist Is For
- Product Managers launching AI-powered features or products
- Founders & CTOs building AI startups or integrating AI into existing products
- Engineering Leaders responsible for delivering AI systems to production
- ML Engineers & AI Researchers transitioning from research to production
- Marketing & Growth Teams positioning and launching AI products
The Complete Checklist
Strategy & Planning
Define your vision, validate your AI use case, understand your market, analyze competition, and create a realistic launch timeline.
Product Definition
Clarify the problem you're solving, design your AI solution, define MVP scope, set success metrics, and prioritize features.
Technical Architecture
Choose your model approach, design system architecture, select infrastructure, plan for scalability, and ensure security.
Data Strategy
Plan data collection, ensure data quality, build processing pipelines, implement privacy measures, and manage datasets effectively.
Development & Integration
Build AI features, integrate with your application, design APIs, implement user interfaces, and create seamless experiences.
Testing & Quality
Test model performance, validate outputs, conduct user testing, benchmark against competitors, and ensure reliability.
Safety & Ethics
Implement bias detection, establish safety measures, ensure compliance, create ethical guidelines, and build responsible AI.
Launch Preparation
Create documentation, set pricing, prepare support systems, plan onboarding, and finalize all pre-launch requirements.
Go-to-Market
Execute your launch strategy, acquire early users, generate buzz, communicate value, and build initial momentum.
Monitoring & Operations
Set up observability, track model performance, implement alerting, create feedback loops, and respond to incidents.
Scaling & Optimization
Optimize performance, reduce costs, improve accuracy, scale infrastructure, and handle increased load efficiently.
Iteration & Growth
Analyze usage data, gather feedback, prioritize improvements, refine your model, expand features, and plan next milestones.
Ready to Launch Your AI Product?
Start with Strategy & Planning to build a solid foundation for your launch.
Begin the Checklist